A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic
Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activ...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zou, Xin [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2020transfer abstract |
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| Übergeordnetes Werk: |
Enthalten in: Biosensors: A novel approach to and recent discovery in detection of cytokines - Mobed, Ahmad ELSEVIER, 2020, an international research journal, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:109 ; year:2020 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.autcon.2019.102990 |
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ELV048576638 |
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| 520 | |a Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. | ||
| 520 | |a Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. | ||
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10.1016/j.autcon.2019.102990 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000819.pica (DE-627)ELV048576638 (ELSEVIER)S0926-5805(18)30940-3 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Zou, Xin verfasserin aut A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Zhang, Lihui oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:109 year:2020 pages:0 https://doi.org/10.1016/j.autcon.2019.102990 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 109 2020 0 |
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10.1016/j.autcon.2019.102990 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000819.pica (DE-627)ELV048576638 (ELSEVIER)S0926-5805(18)30940-3 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Zou, Xin verfasserin aut A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Zhang, Lihui oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:109 year:2020 pages:0 https://doi.org/10.1016/j.autcon.2019.102990 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 109 2020 0 |
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10.1016/j.autcon.2019.102990 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000819.pica (DE-627)ELV048576638 (ELSEVIER)S0926-5805(18)30940-3 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Zou, Xin verfasserin aut A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Zhang, Lihui oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:109 year:2020 pages:0 https://doi.org/10.1016/j.autcon.2019.102990 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 109 2020 0 |
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10.1016/j.autcon.2019.102990 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000819.pica (DE-627)ELV048576638 (ELSEVIER)S0926-5805(18)30940-3 DE-627 ger DE-627 rakwb eng 570 VZ BIODIV DE-30 fid 44.00 bkl Zou, Xin verfasserin aut A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic 2020transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. Zhang, Lihui oth Enthalten in Elsevier Science Publ Mobed, Ahmad ELSEVIER Biosensors: A novel approach to and recent discovery in detection of cytokines 2020 an international research journal Amsterdam [u.a.] (DE-627)ELV004774973 volume:109 year:2020 pages:0 https://doi.org/10.1016/j.autcon.2019.102990 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 44.00 Medizin: Allgemeines VZ AR 109 2020 0 |
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Zou, Xin |
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10.1016/j.autcon.2019.102990 |
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a constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic |
| title_auth |
A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic |
| abstract |
Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. |
| abstractGer |
Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. |
| abstract_unstemmed |
Repetitive projects are characterized by a set of activities that need to be repeated in several units. Optimizing the work sequence between each activity in different units is essential to achieve an effective schedule in terms of time and cost. Most previous studies, however, assumed that an activity can only be executed sequentially from the first unit to the last unit. As such, this paper develops a flexible repetitive scheduling model by integrating soft logic into time-cost tradeoffs. This model allows the same activities in different units to be performed in parallel (all of them are executed concurrently), in sequence (one after the other), or part in parallel and part in sequence. Due to feasible solutions combinatorial explosion, the model applies constraint programming to rapidly find optimal or acceptable approximate solutions. Practicability and effectiveness of the model are verified by an illustrative project and the results show that it can provide more flexibility in minimizing the project duration and/or cost. Future directions may point in incorporating the present model with more realistic settings or other scheduling optimization problems. |
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A constraint programming approach for scheduling repetitive projects with atypical activities considering soft logic |
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https://doi.org/10.1016/j.autcon.2019.102990 |
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Zhang, Lihui |
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2024-07-06T19:13:23.738Z |
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